from models.coupled.vanderpol import *
hv.notebook_extension()

van=get_plot()

van[0]

van

Gif capabilitiues

hmap = hv.HoloMap({i: hv.Curve([1, 2, i]) for i in range(10)})
#hv.output(hmap, holomap='gif', fps=3, backend='matplotlib')
hv.output(hmap, holomap='gif', fps=3, backend='bokeh')
#hv.output(hmap, holomap='gif', fps=3, backend='plotly')

import numpy as np
from holoviews import HoloMap, VectorField
#%load_ext holoviews.ipython
%output filename="Image-Pattern-Gaussian" holomap="gif"

holomap = HoloMap()
steps = np.linspace(-2.5, 2.5, 41)
x,y = np.meshgrid(steps, steps)
sine_rings  = np.sin(x**2+y**2)*np.pi+np.pi
exp_falloff = 1/np.exp((x**2+y**2)/15)

for deg in np.linspace(0, 360, 128, endpoint=False):
    vector_data = np.array([x.flatten()/5., y.flatten()/5., 
                             np.sin(deg*2*np.pi/360)*sine_rings.flatten(),
                             exp_falloff.flatten()]).T
    holomap[deg] = VectorField(vector_data, group='Sine Ring')#.opts(backend='bokeh')
holomap

import os 
name='vanderpol_coupled_standalone1'
path='~/mmy/jup/models/'
os.system(f'jupyter nbconvert {path}{name}.ipynb --to html --output {path}{name}')
os.system(f'jupyter nbconvert {path}{name}.ipynb --to markdown --output {path}{name}')